Using genetically engineered animal models in the postgenomic era to understand gene function in alcoholism.

Over the last 50 years, researchers have made substantial progress in identifying genetic variations that underlie the complex phenotype of alcoholism. Not much is known, however, about how this genetic variation translates into altered biological function. Genetic animal models recapitulating specific characteristics of the human condition have helped elucidate gene function and the genetic basis of disease. In particular, major advances have come from the ability to manipulate genes through a variety of genetic technologies that provide an unprecedented capacity to determine gene function in the living organism and in alcohol-related behaviors. Even newer genetic-engineering technologies have given researchers the ability to control when and where a specific gene or mutation is activated or deleted, allowing investigators to narrow the role of the gene’s function to circumscribed neural pathways and across development. These technologies are important for all areas of neuroscience, and several public and private initiatives are making a new generation of genetic-engineering tools available to the scientific community at large. Finally, high-throughput “next-generation sequencing” technologies are set to rapidly increase knowledge of the genome, epigenome, and transcriptome, which, combined with genetically engineered mouse mutants, will enhance insight into biological function. All of these resources will provide deeper insight into the genetic basis of alcoholism.

D uring the first decade of the new out of this effort. Indeed, sequencing laboratories. These genomic advances, millennium, remarkable advances of the genome of the canonical research coupled with major progress in geneticin technology allowed investigators mouse strain, called C57BL/6, followed engineering technology, are set to sigin all areas of biological research to col-by the sequencing of other inbred mouse nificantly enhance understanding of lect massive amounts of genetic data at strains, has opened major opportunities the genetic basis of human disease, an unprecedented rate. The genomics for a fundamental understanding of including the genetic basis of alcoholism. revolution, which began with the how an organism's genetic makeup An inherited predisposition for sequencing of the human genome, was (i.e., genotype) is related to its observ-alcoholism has been suspected for the basis for efforts such as the 1000 able characteristics (i.e., phenotype). hundreds of years because of the obser-Genomes Project (www.1000genomes. Sophisticated tools for creating geneti-vation that alcoholism tends to run in org) that strive to compile a compre-cally engineered animal models of human families. However, this familial pattern hensive catalogue of genetic variation in diseases also have reached a point where is not direct proof of a genetic vulnerahumans. A catalogue of genetic variation community-centered efforts have begun bility, because it also could be explained across multiple species also was borne to eclipse previous efforts of individual by a shared environment. It was not until the 1970s that this notion was scientifically tested in a systematic fashion, when Goodwin and colleagues (1973) studied the drinking histories of 55 adopted-out sons of alcoholics and 78 adopted-out sons of nonalcoholics, all of whom were adopted within the first 6 weeks of life. It is worth noting that the sons of alcoholics in this study had no knowledge that their biological parents had alcoholism. The results of this analysis were striking: The biological sons of alcoholics who had been adopted by nonrelated foster families were four times as likely to become alcoholics compared with the sons of nonalcoholics. Similar lines of research in twin and family studies convincingly have demonstrated that genetic factors account for between 50 to 60 percent of the vulnerability to alcoholism. However, although this statistic provides compelling evidence for a genetic influence on alcoholism, it does not indicate the specific genes that increase or decrease risk of developing alcoholism. The search for genes associated with a predisposition toward alcoholism began more than 25 years ago. One of the first concerted research efforts to map such genes, the Collaborative Studies on the Genetics of Alcoholism (COGA), was established in 1989. The COGA sample is derived from more than 100 nuclear families densely affected with alcoholism, for whom extensive genotypic as well as phenotypic information has been collected. To date, researchers have identified about 20 genes that contribute to the risk of alcoholism in this sample. Similar studies by investigators all over the world, in a range of different populations, have identified additional genetic variants that contribute to the vulnerability to alcoholism. These genes encode proteins involved in almost all of the major brain-signaling (i.e., neurotransmitter) systems, including the γ-aminobutyric acid (GABA), glutamate, serotonin, dopamine, and acetylcholine systems. Genes involved with alcohol metabolism, other signaling mechanisms (e.g., neuropeptide and neuroendocrine signaling), and cellular architecture also have been implicated (Edenberg and Foroud 2006;Kranzler and Edenberg 2010). Yet, although this work has identified some candidate genes, it is only the first step in gaining insight into the etiology of alcoholism. The next step is to understand how genetic variation alters brain function and to determine which genes are most important for alcoholism and, finally, its treatment.
Understanding how the genotype of an organism is causally related to its phenotype is a fundamental goal of contemporary genetics. Over the last two decades, researchers have developed many innovative approaches to address this issue. Because of practical and ethical limitations associated with research in humans, the major thrust of this work has come from mechanistic studies in animal models of human diseases, particularly the use of genetically engineered animals. Indeed, animal models already have played a crucial role in understanding the genetic basis of alcoholism. The key approach used in these analyses is to manipulate genes in a controlled fashion in animal models in order to elucidate the genes' function(s) in alcohol-related phenotypes. This review highlights recent advances in determining gene function using animal models with relevance to alcohol research. The discussion focuses almost exclusively on mouse models, because numerous novel genetic tools have been accumulating that allow gene manipulation in these models. In addition, this review describes publicly and privately funded community efforts for large-scale genetic engineering and sys-tematic phenotyping. Finally, a brief introduction to novel high-throughput genomic sequencing technologies (e.g., next-generation sequencing) is presented. These technologies have great potential for furthering understanding of how genotype is causally related to phenotype by providing the most comprehensive depiction of the genome, transcriptome, and epigenome ever attempted.

conventional genetic Strategies for Analyzing gene Function
A widely used method to determine the function of a gene suspected of contributing to a certain trait (e.g., alcohol consumption) is to eliminate the gene from the organism under investigation (usually mice) through a method called homologous recombination. The resultant animal is called a null mutant or knockout for that gene. The investigator then determines what effect the absence of the gene (and the protein that it encodes) has on the trait being studied. Another conventional strategy for gene modification that uses the opposite approach to knockouts is called transgenesis. With this technique, a foreign gene (i.e., transgene) is introduced into a recipient organism's genome, resulting in a transgenic animal. The product of the transgene can be produced at higher-than-normal levels (i.e., overexpressed) or otherwise manipulated in the transgenic animal in order to study the gene's function. These approaches have been used extensively in alcohol research, and Crabbe and colleagues (2006) have published a comprehensive literature review covering the first 10 years (1996 to 2006) of studies using genetically engineered mice in this field. In addition, the Integrative Neuroscience Initiative on Alcoholism (INIA) West Consortium maintains a database containing historic and recent studies using genetically engineered mice in alcohol research.
Since 2007, numerous studies have used knockout mice to determine the The search for genes associated with a predisposition toward alcoholism began more than 25 years ago.
effects of specific genes on alcohol consumption, using a standard two-bottle choice procedure in which the animals can freely choose between a water bottle and an alcohol (i.e., ethanol)-containing bottle for drinking (see table 1). In these studies, the knockout animals showed increases and decreases in ethanol drinking, depending on the specific gene that had been deleted. For one of the genes studied-a gene encoding a molecule called the CB1 receptorstudies consistently found that the knockout mice showed reduced ethanol drinking (Hungund et al. 2003;Naassila et al. 2004;Poncelet et al. 2003;Thanos et al. 2005). The results of other studies measuring ethanol consumption in animals in which genes such as those encoding proteins called adiponectin receptor 2, agouti-related protein, neurokinin-1 receptor, PSD-95, and adenylyl cyclase type 5 had been knocked out have yet to be confirmed in independent studies. Nevertheless, these initial findings offer exciting new possibilities for expanding the knowledge of the functional roles of genes associated with alcohol-related traits. For example, in a recent study, a group of neuroimmune genes were examined for their effect on ethanol consumption using knockout mice (Blednov et al. 2011a) (table 1). Previous genomics data measuring gene expression had implicated these genes in the response to alcohol. The results of the knockout studies demonstrate that these genes have a role in regulating alcohol consumption, thereby providing functional evidence supporting the initial gene expression studies. Thus, knockout studies can play a critical role in confirming the findings of other genomic studies and uncovering hitherto unknown molecular targets of ethanol. However, the conventional knockout approach is associated with inherent limitations (for a detailed review of these limitations and ways to circumvent some of them, see Gerlai 1996;Wolfer et al. 2002). Briefly, one of the main limitations of studying conventional knockouts is the issue of developmental compensation. Because the gene of interest is inactivated over the entire lifespan of the knockout animal, changes in gene expression (or another biological response) in another or similar system may occur to compensate for the deleted gene. This compensatory response may obscure the real effects of the knockout on the trait of interest, resulting in falsenegative results. Alternatively, any observed effects may result from the compensatory response rather than the actual gene knockout, leading to a falsepositive effect. Another issue is background strain effects-that is, the effect of the knockout may vary depending on the mouse strain in which the knockout animal was generated. Finally, passengergene effects may occur. This means that during the process of genetically engineering a knockout animal, unintended genetic material can be introduced into the organism along with the genetic material required to create the knockout. These so-called passenger genes also can result in false-negative and false-positive effects. The next section describes some of the strategies used to overcome these limitations.

Understanding gene Function Through conditional Knockout, Knockin, and Viral-mediated Approaches
To overcome the limitations of conventional knockout studies, researchers have devised elegant and creative alternatives. Some of these strategies broadly can be classified as conditional strategies. The term "conditional" refers to the experimenter's ability to impose specific time and space constraints on when and where the knockout or mutant is generated in the organism. This is accomplished, for example, by engineering 284 Alcohol research: C u r r e n t R e v i e w s engineering genetic elements that can be activated (i.e., induced) at a specific time by exposing the animal to a certain chemical agent. Another strategy is to engineer the knockout so that the gene only is deleted when a certain enzyme is present in the cell. By using enzymes that are expressed only in certain cells or tissues, the effects of the gene knockout also only would be limited to those cells or tissues.
Other approaches are using viruses to modify gene expression only in certain tissues. For example, viruses can be used to deliver inhibitory genetic material (referred to as RNA interference [RNAi]) directly to the brain, thereby allowing investigators to selectively reduce or "knockdown" the expression of target genes in specific brain areas. Conversely, viral-mediated approaches can help to overexpress a gene in a specified region.
Finally, as an alternative to eliminating an entire gene from an organism, researchers can introduce mutations into the gene that only change one or several amino acids in the protein that is encoded from the gene and determine the effect of this slight modification on function. This strategy is known as the knockin approach. Recently developed techniques even allow investigators to precisely control the timing and location of the expression of the knockin gene in the organism, resulting in a conditional knockin approach (Skvorak et al. 2006). One example of such a knockin approach, which will be discussed in more detail below, is a mutation in one of the genes encoding a component of the receptor for the neurotransmitter GABA. This modified variant of the GABA A receptor subunit no longer responds to alcohol but retains its function as a GABA receptor. Use of this gene variant has allowed investigators to define the role of specific GABA receptors in the behavioral actions of alcohol without completely deleting the receptors (Blednov et al. 2011b;Harris et al. 2011;Werner et al. 2006). In particular, this approach demonstrated that alcohol acts on the a2 subunit of the GABA A receptor to produce its acti-vating and aversive behavioral effects (Blednov et al. 2011b). This result is intriguing because the gene encoding this subunit previously has been identified as a strong candidate gene for alcohol dependence in humans (Enoch 2008).
Alcohol researchers are just beginning to systematically apply these newer genetic-engineering approaches to their work, and the following paragraphs will illustrate a few recent examples, along with examples from related fields. Studies using the conventional knockout strategy found that global knockout of the gene encoding a brain enzyme called protein kinase C epsilon (PKCe) reduced alcohol self-administration as well as signs of alcohol withdrawal (Hodge et al. 1999;Olive et al. 2000). However, the specific brain region that mediated this effect was unknown, and effects of developmental compensation could not be ruled out conclusively. To address these issues, Lesscher and colleagues (2009) applied a conditional knockout strategy using viral vectors containing RNAi that were delivered directly into a brain region called the amygdala, thereby preventing expression PKCe in that region. Genetic knockdown of PKCe with these viral vectors significantly reduced alcohol consumption (Lesscher et al. 2009), indicating that PKCe expression in the amygdala is important for ethanol consumption in mice. This strategy enabled the investigators to not only rule out the issues of developmental compensation but also to determine the brain region where the PKCe gene exerted its effect.
Using a slightly different conditional knockout strategy, Brigman and colleagues (2010) examined the role of a glutamate receptor subunit in synaptic plasticity and learning, two phenomena that are critically involved in alcoholism. To generate the conditional glutamate receptor knockout animal, the researchers engineered a gene encoding the glutamate receptor subunit NR2B that would be removed only in the presence of a specific enzyme called Cre recombinase. Expression of the Cre recombinase, in turn, was restricted to the cortex and hippocampus by using a genetic element (i.e., promoter) called the CaMKII promoter that only is active in these brain tissues. As a result, deletion of the NR2B gene would be limited to those brain regions in which the CaMKII promoter was active. The NR2B conditional knockout mice showed significant impairments in a form of synaptic plasticity called long-term depression, altered morphology of nerve cells (i.e., neurons), and deficits in a learning task (Brigman et al. 2010). Because the NR2B gene knockout was restricted to the hippocampus and cortex, these brain regions obviously were crucial to the function of the NR2B gene. In addition, these analyses also partially controlled for development-specific factors of the genetic knockout because the CaMKII-driven expression of Cre recombinase occurs late in postnatal development. Thus, this approach eliminates any confounding effects that could be associated with the absence of the NR2B gene during earlier developmental stages.
The knockin strategy to understand gene function also has shown promise. The brain's GABA-mediated (i.e., GABAergic) signaling system has been implicated in alcohol's actions on the brain and also in mediating a genetic predisposition toward alcoholism (Enoch 2008). A recent study (Blednov et al. 2011b) used the knockin strategy to genetically modify the a2 subunit of the GABA A receptor at just two amino acids. Mice carrying this a2 mutant still responded to GABA but failed to show enhanced GABA activity (i.e., potentiation) in response to alcohol. Behaviorally, a2 mutant mice failed to show alcohol-induced conditioned taste aversion and motor stimulation as well as displayed altered alcohol intake and preference. Therefore, using this knockin strategy, the researchers were able to support the a2 subunit's role in specific actions of alcohol (Blednov et al. 2011b). Additional studies in these mice ruled out major developmental compensation effects of the mutated subunit (Harris et al. 2011), further confirm-community resources for high-Throughput genetic engineering As the above examples indicate, geneticengineering techniques hold tremendous power for dissecting the role of specific genes in alcohol-related phenotypes. The generation of genetically modified animals, however, requires a lot of time and resources, which can prevent investigators from creating needed mutant animals. Several communitywide resources have been developed to help facilitate the use of genetically engineered animal models for studying human diseases (table 2). This section briefly describes some of these resources.

The Knockout Mouse Project (KOMP)
Both publicly and privately funded resources are available that aim to facil-itate the use of genetically engineered animals to model human disease and understand gene function. The sequencing of several mouse genomes, including that of the widely used C57BL/6 strain, motivated the development of a resource to elucidate gene function. In 2003, a conference at the Banbury Center at the Cold Spring Harbor Laboratory discussed mouse genomics and genetic engineering, leading to an agreement to begin construction of a collection of mouse knockout mutants for every gene in the mouse genome (Austin et al. 2004). The strategy was to first generate null and conditionalready knockout mutants in embryonic stem (ES) cells, using both gene-targeting and gene-trapping methodology. Next, mice would be generated from these ES cells to characterize the effects of the mutants at multiple levels of analysis,  The KoMP phase 2 (KoMP ) has just been initiated and resources generated by this project will be available in the near future.
these community efforts are coordi-oratories, which also would allow the this study all were conventional knocknated under the International Knockout alcohol research community to benefit outs, and the caveats discussed above Mouse Consortium (IKMC) (http:// greatly from this resource. For example, apply. Thus, although the approach is www.knockoutmouse.org/). an alcohol researcher interested in gene impressive for its large-scale effort in X could obtain broad-based phenotyping systematic phenotyping, it is difficult Knockout Mouse Project Phase 2 data from the central repository for the to draw clear conclusions from it because (KOMP 2 ) knockout mouse generated for gene X, of potential developmental compensawhich would provide basic information tion on the phenotypes displayed by As the community-wide efforts to genon many baseline measures. The invesany particular knockout in this study. erate an extensive collection of null tigator then could design experiments Community-wide efforts are under way and conditional-ready mouse mutants in his or her own laboratory to test the to address some of these limitations. are nearing the completion of their knockout mouse for gene X on more For example, large-scale projects to first phase, they are gearing up to begin specific measures, such as alcohol intake, examine tissue-and cell-type-specific generating mice for phenotyping. For withdrawal severity, and alcohol-induced knockout animals are discussed below. example, the KOMP already has genmotor stimulation. It is clear that this Nonetheless, the study by Tang and erated over 400 null mutant mouse resource will provide an efficient means colleagues (2010) is a seminal account lines and, at the current production for alcohol researchers to discover novel demonstrating the utility of communityrates, is set to produce a total of over genes associated with alcohol dependence. wide efforts to understand gene function 800.

Storage of ES cells and production
Tang and colleagues (2010) recently using large-scale mouse knockout techof mice are coordinated at a central published the results of such a systemnology and systematic phenotyping. repository, which is essential for ensuring atic phenotyping approach using a that investigators rapidly can obtain large-scale mouse knockout library to International Gene Trap Consortium: animals and reagents for their research elucidate gene function. In a tour de An Alternative Approach (http://www.komp.org/). The logistics force, the researchers generated a mouse of the phenotyping phase of the KOMP knockout library of 472 proteins that As mentioned above, the community-(i.e., the KOMP phase 2 [KOMP 2 ]) are either secreted by the cells or span wide effort to generate knockout ES were formalized at a workshop conthe cell membrane (i.e., transmembrane cells for every gene in the mouse includes vened by the NIH in October 2009. proteins). The investigators reasoned both the more common gene-targeting The main recommendation was to that the genes encoding these proteins approach and gene-trapping technolinitiate a coordinated high-throughput would be ideal knockout candidates, ogy. The International Gene Trap phenotyping effort for knockout mice because the proteins are easily accessible Consortium (IGTC) (www.genetrap. generated by the KOMP, EuCOMM, therapeutic targets and understanding org) uses gene-trap technology for and NorCOMM. The first phase of their function would be beneficial for high-throughput mutagenesis to prophenotyping was proposed to be broad drug development. The researchers duce null mutants in mouse ES cells based and conducted by a centralized performed systematic, broad-based (Nord et al. 2006). It uses small DNA phenotyping center. In addition, the phenotyping that encompassed several pieces (i.e., vectors) that simultaneously gene list from the IKMC would be pritherapeutic areas, including embryonic disrupt the target gene at the point of oritized with the aim of discovering development, metabolism, the immune insertion and report the level of expresnew phenotypes rather than confirming system, the nervous system, and the sion of the disrupted gene. Thus, gene already-known knockout phenotypes. cardiovascular system. Almost 90 percent trapping can produce gene variants It was envisioned that the broad-based of the knockout mutants (i.e., 419 (i.e., alleles) that entirely lose their phenotyping program would draw on mutants) showed an observable pheno-function as well as a variety of other examples from other phenotyping efforts type across various organ systems studied. experimental alleles if newer gene-trap across Europe, such as the EmpressSlim Specifically, approximately 30 percent vectors are used that allow for modifimodel at MRC Harwell. This primary (i.e., 150 mutants) exhibited an observ-cation of expression after the insertion. screen would include such phenotypes able phenotype in just one organ sys- The IGTC oversees a repository of all as measures of body weight, locomotem, whereas approximately 60 percent publicly available gene-trap cell lines, tion, pain sensitivity (i.e., nociception), exhibited a phenotype in two or more which are freely available to investigators. and various immunological measures.
systems. This latter finding highlights Initially, there was some skepticism Of particular interest to the alcohol the importance of pleiotropy-that is, regarding the percentage of gene traps research community, neurobehavioral the fact that a single gene can have that could produce true null mutants measures also would be included in this more than one function so that a single and the fraction of the genome that stage. The broad-based phenotyping mutation can give rise to multiple phe-ultimately can be covered by gene-trap then would be followed by more spenotypes. However, it is important to mutations. The first attempts using cialized phenotyping by individual labnote that the mutants generated in this approach estimated a mutational coverage of approximately 60 percent Blueprint initiative (http://www.credriver Cre-expressing line. These Cre reporter of the mouse genome (Skarnes et al. mice.org/index). This project was lines also are useful for mapping neu-2004; Zambrowicz et al. 2003). More motivated by a major bottleneck in ronal circuitry, imaging, and tracking recent attempts, however, have shown the process of establishing Cre/loxP cell populations in the intact organism. more than 90 percent mutational cov-lines-that is, a lack of efficient animal However, although reporter lines are erage of the mouse genome (Gragerov lines in which the Cre gene is under useful as a first approximation of the et al. 2007). Thus, both gene-targeting the control of different promoters (i.e., pattern of Cre-mediated recombinaand gene-trapping approaches are Cre-driver lines) resulting in differention, not all "floxed" reporter genes proving to be efficient high-through-tial patterns of spatial expression, parand target genes yield the same result. put means of generating a community-ticularly in the brain. Establishing For example, the pattern of Cre-mediated wide resource of genetically engineered these lines is particularly challenging recombination sometimes is specific to mice for studies of human disease.
because of the marked differences in the floxed gene, and cautious interpregene expression among various brain tation of reporter line results therefore Cre-Driver Mouse Project regions (Sandberg et al. 2000), and is warranted. Nevertheless, the Allen the Cre-driver network was spawned Institute for Brain Science is continuing Another gene-targeting system that has by the research community's need for a to produce and characterize novel Cre provided investigators with extraordinary resource of Cre-driver lines that can be reporter lines and making this data control of experiments to determine used for spatial/temporal and/or inducible public through an online database gene function in living organisms is knockout studies. To this end, the (http://transgenicmouse.alleninstitute. called the Cre/loxP system, which already NIH Blueprint for Neuroscience org). This resource undoubtedly will was alluded to earlier in this article. It Research funded three centers in the enable investigators to determine the allows for inducible and conditional United States to generate genetically usefulness of various Cre-driver lines for gene targeting in the mouse by engimodified C57BL/6 mice expressing cell-type-specific genetic manipulations. neering the bacterial gene that encodes Cre recombinase in the nervous system. Cre recombinase into a mouse. Expression The resources generated from these The Gene Expression Nervous of the Cre recombinase then can be projects will be made freely available to System Atlas spatially restricted by fusing the gene the neuroscience community. To date, with a cell-or tissue-specific promoter. more than 200 novel Cre-driver lines The Gene Expression Nervous System Cre recombinase recognizes and cuts a have been constructed, and many Atlas (GENSAT) is another remarkable short bacterial DNA segment called a investigators are expected to use this project that aims to catalogue gene-loxP site. These sites can be genetically resource as more Cre-lines are produced. expression patterns of the developing engineered into a separate mouse line Similar Cre-driver-line projects that and adult central nervous system in the (referred to as a floxed line or "condiare funded by private sources also are mouse (http://www.gensat.org/index. tional ready" line), in which the loxP becoming available to the research html). This is accomplished by using a sequences are placed strategically around community. For example, the Allen fluorescent reporter (such as GFP) to a critical genomic region containing a Institute for Brain Science reported replace the coding region of a gene of gene or gene segment of interest. When on a robust and high-throughput interest in a bacterial artificial chromoanimals from the Cre-line are crossed Cre-reporting and characterization some (BAC) that also carries the reguwith animals from the floxed line, the system for the whole mouse brain latory regions (e.g., promoter) required gene or gene segment of interest is (Madisen et al. 2010). for the gene's expression in the brain. excised in a specific cell type or tissue, One of the challenges inherent in These BAC constructs are injected into depending on the promoter used to using the Cre/loxP system for condi-mouse eggs, and transgenic animals control the Cre gene, and researchers tional gene modification is to verify the are generated. Using fluorescence can study the resulting effects.
actual pattern of deletion of the gene microscopy, investigators then can As mentioned earlier, this system has of interest. This problem partially can visualize where the reporter gene is been used to elucidate the function of be resolved by genetically engineering expressed, which reflects the natural a glutamate receptor subunit by using the mice so that they also express an expression of the gene of interest. To a cell-type-specific promoter to drive easily measurable reporter gene (e.g., date, over 500 genes have been ana-Cre recombinase expression in a b-galactosidase or a fluorescent probe lyzed using this approach. This atlas restricted brain area. In addition, the such as green fluorescent protein [GFP]) of brain gene expression has significant Cre/loxP system has been used in several that is activated after Cre-mediated implications for understanding the community-wide efforts to analyze gene excision of a transcriptional stop signal. great variety of neuronal cell types function. One such key community- The expression of the reporter gene (Gong et al. 2003). In addition to being wide project is the Cre-driver network then can be visualized in the brain as a community resource for cataloging established by the NIH Neuroscience a measure of the deletion pattern of a cell-type-specific gene expression in the brain, GENSAT has targeted Cre recombinase to specific neuronal populations using the BAC approach (Gong et al. 2007), thereby allowing investigators to use the lines for genetic manipulations, such as producing inducible or conditional knockout mice.

high-Throughput Novel genomic Sequencing
Although substantial progress has been made in identifying some of the genes associated with the risk for alcoholism, much of the genetic variation that contributes to alcoholism has yet to be identified because of the heterogeneous nature of the disease. However, the advent of novel high-throughput genomic-sequencing technologies that have become available within the last decade likely will accelerate this progress. These new sequencing technologies are termed "next-generation sequencing," to distinguish them from the conventional sequencing technologies developed in the 1970s. The greatest improvements in these new technologies are massive increases in speed and an exponential drop in cost to sequence. Thus, next-generation sequencing machines can read up to 250 billion DNA building blocks (i.e., bases) per week, compared with approximately 25,000 per week using conventional sequencing. In addition, the price per base for sequencing has dropped approximately 100,000-fold over the last decade, which makes next-generation sequencing a realistic application for all areas of biology, including sequencing of large cohorts of humans and other experimental organisms. This new approach also has the power to rapidly uncover variation in non-protein-coding regions of the genome (e.g., regulatory regions or microRNAs) and to characterize all isoforms of a particular gene by detecting alternatively spliced variants. 1 Another application of this new technology will be the complete depiction of the transcriptome and epigenome, which will have important implications for understanding how the genome functions in normal and pathophysiological conditions such as alcoholism. Creating comprehensive whole-genome maps that contain detailed information on genomic, epigenomic, and transcriptomic variation associated with alcohol dependence would greatly advance the alcohol research field. With the advances in sequencing technologies and the resulting acceleration of data generation, the rate-limiting step of fully realizing the potential of this information now has become data analysis and bioinformatics, and it is quite clear that novel analytical approaches must be developed for meaningful data interpretation. An obvious way to address this issue would be to use a systems-based approach to interpret genomic data, including novel methods to analyze and detect genegene interactions (i.e., epistasis). In addition, because complete genomic information (including noncoding regulatory regions) will be at hand, novel methods to understand gene regulation are essential.
Finally, another important variable in determining vulnerability to alcohol dependence is the environment. Environmental factors can contribute as much as one-half of the total risk for developing alcoholism. However, this has not been studied systematically in relationship to gene-by-environment interactions, at least in part because of an incomplete knowledge of the genome. Next-generation sequencing, with its massive output of genomic data, likely will change this scenario by providing a foundation on which the effects of environmental perturbations can be assessed on a grand scale.

An exciting Future for Alcohol genetics
The postgenomic era has seen the development of global efforts to understand the function of the genome. Over the last 10 years, international research consortia have been created to tackle this enormous task, and this model is proving to be efficient for highthroughput science. In particular, concerted efforts to knock out every gene in the mouse genome are succeeding because of the use of focused resource centers. The alcohol research community is just beginning to use these resources and stands to benefit greatly from them. For example, with the availability of knockout lines for every gene, it will be possible to define the genes responsible for specific actions of alcohol. In addition, readily available conventional and conditional knockout animals will advance quantitative trait locus mapping studies. In particular, conditional knockout studies will become more abundant in the alcohol research community, allowing investigators to avoid some of the major interpretative difficulties associated with the conventional knockout studies that have dominated in the last 15 years.
Another exciting possibility is the use of new animal genetic-engineering techniques to reproduce specific genetic changes seen in human alcoholics. For example, as described above, detailed genetic sequencing of both DNA and RNA (i.e., the genome and transcriptome) from many humans now is feasible, owing to the rapidly decreasing cost of next-generation DNA sequencing. This will lead to the discovery of changes in gene sequence or gene expression that are candidates for differences in the development of alcohol dependence. These same genomic changes then can be introduced into mice or other animal models by knockin, transgenic, or other approaches (see figure). This approach already has shown promise in the alcohol field. For example, one of several variants (i.e., polymorphism) of the gene encoding the m-opioid receptor is associated with enhanced subjective responses to alcohol in humans and differentially affects treatment response to naltrexone (Ray and Hutchinson 2007). To directly deter-subjective responses to alcohol in humans and differentially affects treatment response to naltrexone (Ray and Hutchinson 2007). To directly determine the functional consequences of this polymorphism, a knockin mouse was generated that harbors the human allele. The results indicate that the knockin mouse shows a greater brain dopamine response after alcohol challenge, possibly providing a mechanism by which the human variant of the µ-opioid receptor affects drinking (Ramchandani et al. 2010). Additional characterization of this "humanized" mouse model surely will provide important information about the functional consequences of this polymorphism on alcohol behaviors.
Besides generating mice with humanspecific polymorphisms in known genes via the knockin approach, genetic engineering could be used to manipulate the vast array of noncoding regions of the genome that are copied into mRNA (i.e., are transcribed) but do not encode a specific protein. For example, recently discovered large noncoding RNAs (lncRNAs) are known to have a critical role in maintaining the state of the DNA-protein complex (i.e., chromatin) that makes up the chromosomes. Chromatin states influence gene expression on a fundamental level (Khalil et al. 2009). Although it has not been attempted yet, genetically manipulating these lncRNAs in an animal model could uncover significant functional roles in alcohol-related behaviors.
Finally, the human and mouse genomes are estimated to contain approximately 25,000 genes. However, the number of alternative forms of these known genes (i.e., alternatively spliced variants) may be about 10 times this amount, creating substantial genomic diversity with unknown function. Genetic manipulation of the roughly 200,000 alternatively spliced gene variants has not been explored systematically. This area also holds tremendous potential for discovering novel relationships between genotype and phenotype by generating genetically engineered animal models with alternatively spliced gene variants. Given 290 Alcohol Research: C u r r e n t R e v i e w s

Figure
Exploring the relationship between genotype and phenotype by using high-throughput sequencing and genetically engineered animal models. Novel high-throughput "next-generation sequencing" technology can be used together with new genetic engineering technology to understand gene function in alcoholism. Compared with traditional sequencing, "next-generation sequencing" allows researchers to efficiently and cost-effectively obtain large amounts of genomic data (e.g., from large cohorts of humans with and without disease) to detect all the genomic, epigenomic, and transcriptomic variation associated with the disease, creating comprehensive "disease maps." In a next step, functional information can be attached to these disease maps that defines how the various components of the map (i.e., individual genes) act and interact, for example, using genetically engineered animal models. Genomic variations associated with human diseases can be engineered into rodent models (or other experimental organisms) and detailed phenotypic analyses can be performed, further refining disease maps with functional annotation.
understanding the genetic basis of alcoholism are on the horizon. ■

Financial Disclosure
The authors declare that they have no competing financial interests.